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daylighting-design

Calculate daylight metrics and analyze solar geometry with Python libraries.

277|54|Updated Apr 6, 2026
Search Tags:#daylighting#building design#solar geometry#daylight metrics#daylighting strategies#glare control#artificial lighting
One-click install
npx skills add https://github.com/Abhinavbwj/Skills-Architects --skill daylighting-design-abhinavbwj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: daylighting-design
Source: https://github.com/Abhinavbwj/Skills-Architects/tree/main/skills/daylighting-design
Command: npx skills add https://github.com/Abhinavbwj/Skills-Architects --skill daylighting-design-abhinavbwj

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, pandas, numpy, matplotlib, pypdf, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides comprehensive knowledge and tools for optimizing building daylighting, addressing visual comfort, glare control, and energy efficiency through daylighting strategies and solar geometry calculations.

Core Features & Use Cases

  • Daylight Metrics Calculation: Calculate Daylight Factor (DF), Spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), and other metrics for daylighting performance evaluation.
  • Daylighting Strategies: Explore various daylighting strategies including side-lighting, top-lighting, atriums, light shelves, clerestory windows, and more for different architectural applications.
  • Solar Geometry and Shading: Calculate solar position, design shading devices like overhangs and fins, and analyze shading effects on building facades.
  • Glare Control: Assess glare sources, calculate Daylight Glare Probability (DGP), and implement glare control strategies.
  • Artificial Lighting Integration: Design lighting zones, implement daylight-linked dimming, and optimize for circadian lighting.
  • Daylighting Design Process: Follow an eight-step workflow for successful daylighting design, including establishing performance targets, orienting the building, sizing windows, designing shading devices, selecting glazing, and more.
  • Exemplar Buildings: Reference real-world case studies for each daylighting strategy.

Quick Start

Calculate the Daylight Factor for a room with a single 3 m x 1.8 m window located 2.7 m above the floor.

df = calculate_daylight_factor(window_height=3, window_width=1.8, room_depth=4.5, window_head_height=2.7)
print(df)

Frequently Asked Questions about daylighting-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate daylight metrics like Daylight Factor and Spatial Daylight Autonomy for building design?▼

You can calculate daylight metrics such as Daylight Factor (DF), Spatial Daylight Autonomy (sDA), and Annual Sunlight Exposure (ASE) using Python scripts that process room dimensions and window parameters to evaluate daylighting performance.

What is the best way to design shading devices and analyze solar geometry for building facades?▼

The best way to design shading devices is by calculating solar position and analyzing shading effects on building facades using Python, allowing you to design overhangs and fins for optimal glare control and daylighting.

How do I implement glare control and calculate Daylight Glare Probability in my architectural project?▼

You can implement glare control by assessing glare sources and calculating Daylight Glare Probability (DGP) using Python libraries, enabling you to apply effective glare control strategies for visual comfort.

Can I use Python with pandas and numpy to integrate artificial lighting with daylighting strategies?▼

Yes, you can use Python with pandas and numpy to design lighting zones, implement daylight-linked dimming, and optimize circadian lighting, integrating artificial lighting seamlessly with your daylighting strategies.

What is the step-by-step daylighting design process for optimizing visual comfort and energy efficiency?▼

The daylighting design process follows an eight-step workflow including establishing performance targets, orienting the building, sizing windows, designing shading devices, and selecting glazing to optimize visual comfort and energy efficiency.

Do I need matplotlib to visualize daylighting performance data and building solar geometry calculations?▼

Yes, you need matplotlib alongside pandas and numpy to visualize daylighting performance data, plot solar geometry calculations, and generate graphical outputs for building design analysis.

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